FMCW Lidar Waveform Variation for Noise Rejection
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Solution Overview
Problem
FMCW lidar systems face challenges in accurately separating noise spikes from return signals due to external and internal noise sources, leading to reduced signal-to-noise ratios and decreased accuracy, which affects their suitability for automotive applications.
Innovation Solution
The method involves varying waveforms across frames by changing the frequency or amplitude modulation of transmit signals for consecutive frames, allowing the lidar system to distinguish between noise and return signals more effectively, thereby improving signal-to-noise ratios and accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the lidar system uses a fixed waveform for transmit signals, then the system operation is simple, but the accuracy of separating return signals from noise spikes deteriorates
Solution Approach 1:
The patent applies dynamics by making the waveform parameters (frequency modulation or amplitude modulation) variable across frames rather than fixed. The transmit signal waveform changes dynamically from frame to frame, allowing the system to distinguish return signals from noise spikes through temporal variation in beat frequency patterns.
Solution Approach 2:
The patent implements parameter changes by modifying frequency modulation or amplitude modulation parameters of the transmit signal across different frames. This causes the beat frequency of return signals to vary predictably between frames, while noise spikes remain stationary, enabling accurate separation through frequency analysis.
2Reliability
If the lidar system uses varying waveforms across frames, then the signal-to-noise ratio improves, but the device complexity increases
Solution Approach 1:
The system uses dynamic waveform variation across frames to improve signal-to-noise ratio. By changing frequency or amplitude modulation parameters between frames, return signals produce varying beat frequencies that can be distinguished from stationary noise spikes, thereby improving reliability.
Solution Approach 2:
The patent changes modulation parameters of the transmit signal across frames to enhance signal-to-noise ratio. The frequency or amplitude modulation parameters are varied systematically, causing return signal beat frequencies to shift while noise remains constant, enabling effective noise rejection.
3Measurement precision
If the lidar system processes multiple frames with different waveforms, then the accuracy of range and range-rate determination improves, but the processing time increases
Solution Approach 1:
The patent employs periodic action by systematically varying the waveform parameters across frames in a periodic manner. This allows the system to process multiple frames efficiently, where the periodic waveform variation creates predictable beat frequency patterns that can be analyzed to determine range and range-rate with high accuracy.
Solution Approach 2:
The system uses dynamic waveform adjustment across frames to improve measurement precision while managing processing time. The temporal variation in waveform parameters creates distinct beat frequency signatures for return signals versus noise, enabling accurate range and range-rate determination through efficient frequency analysis.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enhances the accuracy of range, range-rate, and angular information determination, allowing for faster frame rates and improved confidence in associating return signals with their corresponding pixels, thus enabling more accurate and timely data collection for automotive applications.
Implementation Method 1
Frequency-modulated continuous-wave (FMCW) lidar is a promising technology for next-generation autonomous-driving sensors
Implementation Method 2
direct measurement of range and range rate for nearby objects
Implementation Method 3
measuring a return signal reflected from the object
Implementation Method 4
The method determines a beat frequency of the return signal for each frame by mixing the return signal with the transmit signal
Data Source
AI summary
This document describes techniques and systems to vary waveforms across frames in lidar systems. The described lidar system transmits signals with different waveforms for the same pixel of consecutive frames to avoid a return signal overlapping with a noise spike or a frequency component of another return signal. The different waveforms can be formed using different frequency modulations, different amplitude modulations, or a combination thereof for the same pixel of consecutive frames. The lidar system can change the waveform of the transmit signal for the same pixel of a subsequent frame automatically or in response to determining that a signal-to-noise ratio of the return signal of an initial frame is below a threshold value. In this way, the lidar system can increase the signal-to-noise ratios in return signals. These improvements allow the lidar system to increase its accuracy in determining the characteristics of objects that reflected the return signals.